1. Field of the Invention
Embodiments of the present invention relate, in general, to bias stability and more particularly, to methods and systems for detecting bias errors in a signal-processing path.
2. Relevant Background
In engineering, “bias” is the systematic deviation from a reference value. It is a prejudice or an amount by which the average set of values departs from a reference value. It can also be considered to be the predicted difference on average between the measurement and the true value. A closely related topic in engineering is “stability.” Stability is the ability of a measuring instrument to retain its calibration over a long period of time. Stability, therefore, determines an instrument's consistency over time. Accordingly, a bias stability is whether a predicted value, different from the true value, is consistent over time. Unfortunately, it is well-known that bias errors in signal path processing are unstable.
To measure the bias, one must take a long sequence of data and find the average value of that data. Then, when the bias value is known, one can determine a bias stability, which is the change in the bias measurement at a different instant in time. For example, what would the bias be if we took data two hours from now? To measure bias stability, we need to measure the bias at many different points in time and see how the bias changes during that time. But even this leaves some question unanswered: for example, how long should we average the data, and how many times should we measure the bias to make a valid measurement of the bias stability, and so on.
These types of errors occur in many systems, including signal processing. Signal processing is an enabling technology that encompasses the fundamental theory, applications, algorithms, and implementations of processing or transferring information contained in many different physical, symbolic, or abstract formats. These formats are broadly designated as signals, and use mathematical, statistical, computational, heuristic, and linguistic representations, formalisms, and techniques for representation, modeling, analysis, synthesis, discovery, recovery, sensing, acquisition, extraction, learning, security, or forensic analysis. Beyond the errors introduced from a sensor of a similar data collection device, the very path through which the signal passes can assert a certain bias to the observed data. Moreover, the bias (or predicted difference) varies between the data's true value and its observed value. That means that the signal processing path bias is not stable. Therefore, a need exists to determine and account for signal processing path bias and changes that may occur to that bias over time. These and other deficiencies of the prior art are addressed by one or more embodiments of the present invention.
Additional advantages and novel features of this invention shall be set forth in part in the description that follows, and in part will become apparent to those skilled in the art upon examination of the following specification or may be learned by the practice of the invention. The advantages of the invention may be realized and attained by means of the instrumentalities, combinations, compositions, and methods particularly pointed out in the appended claims.